This project uses a Convolutional Neural Network (CNN) to recognize captchas. The model is implemented using PyTorch and the captcha dataset is generated using the captcha library.

• model.py: Contains the definition of the CNN model.
• datasets.py: Contains functions for generating and preprocessing the captcha dataset.
• eval.py: Contains functions for testing the model on a single image or on a test dataset.
• run.py: The main script for training the model.
• data: Include train data and test data
• checkpoint: Save the checkpoint in your worknames directory

You can install all the dependencies using the following command:

pip install -r requirements.txt

You can generate the dataset using the following command:

python datasets.py --data_size {} --test_ratio {}

You can train the model using the following command:

python run.py --workname {} --epochs {}

You can test the model on a single image or on the test dataset using the following command:

python eval.py --modelpath {} --mode test_model python eval.py --modelpath {} --mode test_picture --picpath {}

The following image shows the performance of the model:

https://blog.csdn.net/lijj0304/article/details/132446975